A template for parallelizing the louvain method for modularity maximization

Sanjukta Bhowmick, Sriram Srinivasan

Research output: Chapter in Book/Report/Conference proceedingChapter

8 Scopus citations

Abstract

Detecting communities using modularity maximization is an important operation in network analysis. As the size of the networks increase to petascales, it is important to design parallel algorithms to handle the large-scale data. In this chapter, a shared memory (OpenMP-based) implementation of the Louvain method, one of the most popular algorithms for maximizing modularity, is introduced. This chapter also discusses the challenges in parallelizing this algorithm as well as metrics for evaluating the correctness of the results. The results demonstrate that the implementation is highly scalable. Moreover, it also focuses on how this template can be extended to time-varying networks.

Original languageEnglish (US)
Title of host publicationModeling and Simulation in Science, Engineering and Technology
PublisherSpringer Basel
Pages111-124
Number of pages14
DOIs
StatePublished - 2013

Publication series

NameModeling and Simulation in Science, Engineering and Technology
Volume55
ISSN (Print)2164-3679
ISSN (Electronic)2164-3725

ASJC Scopus subject areas

  • Modeling and Simulation
  • Engineering(all)
  • Fluid Flow and Transfer Processes
  • Computational Mathematics

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    Bhowmick, S., & Srinivasan, S. (2013). A template for parallelizing the louvain method for modularity maximization. In Modeling and Simulation in Science, Engineering and Technology (pp. 111-124). (Modeling and Simulation in Science, Engineering and Technology; Vol. 55). Springer Basel. https://doi.org/10.1007/978-1-4614-6729-8_6